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Data from Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma

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<div>Abstract<p><b>Purpose:</b> To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).</p><p><b>Experimental Design:</b> One-hundred and eighteen patients (training cohort: <i>n</i> = 88; validation cohort: <i>n</i> = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps.</p><p><b>Results:</b> The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; <i>P</i> < 2.68 × 10<sup>−9</sup>). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; <i>P</i> < 1.60 × 10<sup>−7</sup>). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages.</p><p><b>Conclusions:</b> Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies. <i>Clin Cancer Res; 23(15); 4259–69. ©2017 AACR</i>.</p></div>
Title: Data from Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma
Description:
<div>Abstract<p><b>Purpose:</b> To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).
</p><p><b>Experimental Design:</b> One-hundred and eighteen patients (training cohort: <i>n</i> = 88; validation cohort: <i>n</i> = 30) with advanced NPC were enrolled.
A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI.
Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms.
Nomogram discrimination and calibration were evaluated.
Associations between radiomics features and clinical data were investigated using heatmaps.
</p><p><b>Results:</b> The radiomics signatures were significantly associated with PFS.
A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone.
One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system.
This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.
761 vs.
0.
514; <i>P</i> < 2.
68 × 10<sup>−9</sup>).
Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.
776 vs.
0.
649; <i>P</i> < 1.
60 × 10<sup>−7</sup>).
Calibration curves showed good agreement.
Findings were confirmed in the validation cohort.
Heatmaps revealed associations between radiomics features and tumor stages.
</p><p><b>Conclusions:</b> Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC.
These results provide an illustrative example of precision medicine and may affect treatment strategies.
<i>Clin Cancer Res; 23(15); 4259–69.
©2017 AACR</i>.
</p></div>.

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